1. Field of the Invention
The present invention relates to video segmentation, and more specifically, to a method of detecting news anchor persons for dividing news broadcasts into segments.
2. Description of the Prior Art
As there are more and more news channels available on television, the amount of news content available is growing. Accordingly, it is becoming harder for people to search and index the news broadcasts. News programs are composed of several different news segments which are often not related to one another. In order to aid in indexing and categorizing news segments, it is helpful to utilize video images of a news anchor person to determine when segments begin and end. News anchor person shots are the most important shots in the structure of every news segment. Usually, the news anchor person is shown in the beginning and/or the end of a story to introduce, summarize, or comment on the story. These shots of the news anchor persons are useful for providing the main idea of the news story and for enabling a viewer to browse a video recording of the news. As a result, news anchor person detection is a logical way to help identify news segments.
In the past, prior art methods for television news segmentation have used machine learning technology for automatically classifying the news. However, editing effects such as split screens showing data from different sources will limit the performance of these prior art methods. Other methods use complex algorithms such as face detection and speaker identification because both the anchor persons and their positions are unknown. A brief list of other previous techniques is head detection, talking mouth detection, speech and music classification or recognition, closed-caption extraction and video optical character recognition (OCR), and model-based methods. Unfortunately, the computational complexity of each of these algorithms is prohibitively high.